Classification of Immission Measurements 2000 to 2020 in Baden Wuerttemberg

location of selected sampling stations

20 sampling stations operated by LUBW (Landesanstalt für Umwelt Baden-Wuerttemberg) have been selected for analysis of concentrations of atmospheric constituents.In addition 2 stations operated by the city of Stuttgart “Amt für Umweltschutz”.

ID name Messstelle Ost_UTM Nord_UTM
47650 Alb Schwäbische Alb 515300 5354700
4467 Sws Schwarzwald-Süd 407500 5295900
76118 Odw Odenwald 482100 5479100
76359 Lbg_Friedr Ludwigsburg Friedrichstraße 513900 5415100
76364 Rt_leder Reutlingen Lederstraße-Ost 515500 5370700
76361 Nck Stuttgart Am Neckartor 514000 5403900
39253 Brn Bernhausen 516700 5391600
4445 Eggenstein Eggenstein 456600 5436100
4462 Frei Freiburg 412800 5317100
4471 Friedri Friedrichshafen 536500 5278600
4453 Heid Heidelberg 476500 5474100
4461 Heil Heilbronn 516300 5445800
4463 Lbg_weimar Ludwigsburg 512600 5416200
4470 Rt_pomol Reutlingen 515300 5370600
4452 Stuttgart-Bad Cannstatt Stuttgart-Bad Cannstatt 516800 5406200
55006 Stgt_Klett Stuttgart Arnulf-Klett-Platz 513200 5403300
9999136 Hauptst_str Stuttgart Hauptstätter Straße 512500 5401500
9999137 Stg_Stadtg Stuttgart Stadtgarten 512600 5403100
4473 Man_Mitte Mannheim-Mitte 462100 5480400
76362 Stuttgart Hohenheimer Straße Stuttgart Hohenheimer Straße 513500 5401700
xxx Schwabenzentrum Schwabenzentrum NA NA
xx1 Amt_Umwelt Amt Umweltschutz NA NA

3 sampling stations are located in rural environment, 7 stations located at main streets, 10 sampling urban background immissions. In addition 2 stations operated by the city of Stuttgart one located downtown on top of a building about 20 m above the street level the second at the office building in urban background. An overview of the locations:

## # A tibble: 22 × 5
##    ID    name       Messstelle                  Ost_UTM Nord_UTM
##    <fct> <fct>      <fct>                         <dbl>    <dbl>
##  1 47650 Alb        Schwäbische Alb              515300  5354700
##  2 4467  Sws        Schwarzwald-Süd              407500  5295900
##  3 76118 Odw        Odenwald                     482100  5479100
##  4 76359 Lbg_Friedr Ludwigsburg Friedrichstraße  513900  5415100
##  5 76364 Rt_leder   Reutlingen Lederstraße-Ost   515500  5370700
##  6 76361 Nck        Stuttgart Am Neckartor       514000  5403900
##  7 39253 Brn        Bernhausen                   516700  5391600
##  8 4445  Eggenstein Eggenstein                   456600  5436100
##  9 4462  Frei       Freiburg                     412800  5317100
## 10 4471  Friedri    Friedrichshafen              536500  5278600
## # … with 12 more rows

As example of NO2 1-h mean values, measured at Stuttgart- Bad Cannstatt at the roadside are shown in the plot “NO2-immissions 20 years”. The 1- h means are plotted together with red linear regression line over 20 years:

Stg_Can

The following should be noted:
– the immissions vary annually with maximum in winter month – average immissions are reduced with a rate of about \(0.4 [μg/m^3]per year\) – there are long periods without zero 1-h measurements (2016 to 2018) and others reaching zero over longer time periods(2001) – outliers indicate a strong variation of the immissions at the location of the sampling instrument

These observations need to be taken into account with interpretation of the data.

Key immissions data from 23 sampling stations

Mean values, variance and median of \(NO_2\) and \(O_3\) concentrations are very different for the 22 stations analyzed:

Station NO2_mean NO2_median NO2_var WG_mean WG_var O3_mean O3_median O3_var
Sws 3.0 2.0 11.9 2.4 15.2 75.0 73 366.8
Alb 7.1 5.0 50.4 3.3 4.7 67.3 66 874.9
Odw 10.7 8.0 85.3 2.0 1.9 66.1 62 1014.5
Frei 20.5 16.0 234.5 1.7 1.8 51.3 51 1291.8
Egg 23.5 20.0 252.0 2.4 3.6 42.0 38 1248.5
Fri 24.2 21.0 242.8 1.0 0.8 44.1 40 1189.0
Rt_pomol 25.7 22.0 298.5 1.3 0.8 46.6 45 1114.4
Stg_SZ_afu 25.9 22.8 231.7 1.7 0.9 NA NA NA
Heid 27.6 25.0 283.5 1.5 0.9 45.0 41 1138.0
Stg_Stadtg 27.8 22.0 353.8 NA NA NA NA NA
Lbg_weimar 28.1 24.0 375.6 1.8 1.2 45.5 42 1305.0
Stg_Schwz 28.1 25.0 287.5 1.6 0.8 NA NA NA
Brn 30.8 26.0 419.4 1.6 1.8 40.8 37 1165.5
Heil 30.9 27.0 404.5 1.5 1.3 40.2 34 1319.1
Stg_Can 31.6 29.0 364.2 1.1 0.6 40.8 35 1256.2
Man_Mitte 34.2 30.0 441.2 1.5 1.2 NA NA NA
Stg_Hpt 44.1 41.0 412.3 NA NA NA NA NA
Lbg_Friedr 54.4 52.0 661.6 NA NA NA NA NA
Stg_Klt 64.0 59.0 995.7 NA NA 64.3 45 3884.1
Rt_leder 70.1 66.0 1258.9 NA NA NA NA NA
Stg_Hoh 78.9 71.0 2094.1 NA NA NA NA NA
Stg_Nck 87.5 79.0 2422.1 NA NA NA NA NA

The table is arranged in ascending order of mean NO2 immissions measurements calculated from 1-h measurements recorded and published by LUBW (Landesanstalt für Umwelt Baden Wuerttemberg). The mean calculated on the 20 year interval of all recorded data.
–in rural environment immissions are less than \(10 [μg/m^3]\).
urban background immissions range from \(10 [μg/m^3]\) to \(30 [μg/m^3]\).
–immissions close to main traffic streets are bigger than \(40 [μg/m^3]\).

Some observations from the trend :

– average immissions at the three rural stations stay below \(10 [μg/m^3]\)
– at the rural stations the mean ** $mean NO_2 $ ** values are independent of the time – the regression lines (20 year mean) from stations located in urban background
are in between \(25 [μg/m^3]\) and \(40 [μg/m^3]\) – at background stations rate of reduction of $mean NO_2 $ ** is low** compared with traffic stations
– at main streets (heavy traffic) the reduction per year of $mean NO_2 $ is high
– 20-year $mean NO_2 $ exceeded limits considered dangerous to human health close to main streets – at Stuttgart “Am Neckartor” the highest $mean NO_2 $ were recorded
— starting in 2003 with annual mean greater \(125 [μg/m^3]\) which were reduced to \(50 [μg/m^3]\)in 2020
— long trend “Am Neckartor” indicates levels smaller \(40 [μg/m^3]\) – at some stations the rate of reduction (chg_py) is higher than at the station “Am Neckartor”

rate of immission reductions

##    datetime 
## -0.05078936
Station chg_py
Stg_Hpt -5.1
Stg_Schwz -5.0
Stg_Nck -4.3
Rt_leder -4.0
Stg_Hoh -3.6
Stg_SZ_afu -2.8
Lbg_Friedr -2.8
Stg_Klt -1.9
Stg_Stadtg -0.9
Man_Mitte -0.6
Lbg_weimar -0.6
Heid -0.5
Stg_Can -0.4
Heil -0.4
Rt_pomol -0.3
Brn -0.3
Egg -0.3
Fri -0.2
Frei -0.2
Odw -0.1
Alb -0.1
Sws 0.0

The mean yearly reductions ranges from \(-5.1[μg/(m^3*y)]\) at the “Hauptstätter Strasse” and no change at all \(0 [μg/(m^3*y)]\) at the rural background station “Schwarzwald-Süd”.

##           Length Class  Mode
## Alb        9     -none- list
## Sws       10     -none- list
## Odw       10     -none- list
## Brn        6     -none- list
## Lbg        5     -none- list
## Rt         9     -none- list
## Stg.Nck    2     -none- list
## Stg.Hpt    2     -none- list
## Stg.Can    8     -none- list
## Stg.Klt    4     -none- list
## Rt.l       3     -none- list
## Lbg.fr     2     -none- list
## Stg.Hoh    2     -none- list
## Man_Mitte  9     tbl_df list
## Joining, by = c("station", "datetime")
## Joining, by = c("station", "datetime")
## Joining, by = c("station", "datetime")
## [1] 8
## `geom_smooth()` using formula 'y ~ x'

## Effect of Heating on $NO_2, NO, O_3

dat_path<- "~/documents/Luftqualitaet/Daten/BW_Rdat"
load(file.path(dat_path,"BW.RData"))
summary(BW.all_data)
##           Length Class  Mode
## Alb        9     -none- list
## Sws       10     -none- list
## Odw       10     -none- list
## Brn        6     -none- list
## Lbg        5     -none- list
## Rt         9     -none- list
## Stg.Nck    2     -none- list
## Stg.Hpt    2     -none- list
## Stg.Can    8     -none- list
## Stg.Klt    4     -none- list
## Rt.l       3     -none- list
## Lbg.fr     2     -none- list
## Stg.Hoh    2     -none- list
## Man_Mitte  9     tbl_df list
Can_data<-BW.all_data$Stg.Can$Stg.Can.no2 %>% left_join(BW.all_data$Stg.Can$Stg.Can.no)
## Joining, by = c("station", "datetime")
Can_data<-Can_data%>% left_join(BW.all_data$Stg.Can$Stg.Can.temp)
## Joining, by = c("station", "datetime")
Can_data<-Can_data%>%left_join(BW.all_data$Stg.Can$Stg.Can.o3)
## Joining, by = c("station", "datetime")
Can_data_list<-BW.all_data$Stg.Can
Can_comps<-names(BW.all_data$Stg.Can)
length(Can_comps) #8
## [1] 8
Can_tbl<- BW.all_data$Stg.Can$Stg.Can.no2%>% dplyr::select(-NO2)
for (i  in 1:8) {
  df <- BW.all_data$Stg.Can[[i]]
  Can_tbl <- left_join(Can_tbl,df, by=c("station", "datetime"))
}
Can_tbl<-Can_tbl%>% mutate(Hzg = as_factor(ifelse(Temp<= 15,"heating", "no_heating")))
comps <- names(Can_tbl)%>%setdiff(c("station","datetime","Hzg"))
Can_tidy<- Can_tbl%>% pivot_longer(cols = all_of(comps),names_to = "comp",values_to =   "value" )
# Plot
Can_tidy %>% na.omit()%>% filter(comp!= "WR"& comp != "WG"& comp != "CO"& comp != "SO2") %>%
  ggplot(aes(x = datetime))+
  geom_smooth(method = "lm",mapping = aes(y= value,col= comp))+
  facet_grid(.~Hzg)+
  theme(axis.text.x = element_text(angle = 90, hjust = 1))+
  ggtitle(" 21-Year-Trend(regression)
NO, NO2, O3, Temperature",
          subtitle = "Heating hours Stgt.-Bad Cannstatt")+
  labs(x= "", y = "Values(μg/m3,m/s,°C)")
## `geom_smooth()` using formula 'y ~ x'

distribution of heating hours

To visualize the effect of energy burned to heat individual homes, offices and public buildings the demand of heating expressed by the temperature difference \(Grdz = 20- Temp [°C]\) Room temperature an outside Temperature is classified into 4 groups: - no heating necessary \(no.ht\)
- low heating \(low.ht\)
- medium heating \(medium.ht\) - maximum heating \(max.ht\)

Within 21 years (183960 hours) about one third ~ 60000 hours no heating was necessary, low energy consumption was necessary at about 80000 hours, medium with ~ 20000 hours and maximum only for a very small number of hours.

Comparison with emission data

The graph shows the emissions reported to or calculated by the German Umweltbundesamt (UBA). The regression lines the average reduction of total emissions and the contribution of transport and road transport. The main reason for the reduction of transport emissions were improvements were progress with combustion engines and intensive treatment of exhaust gases at power plants and industry. the latter took place mainly 2000 to 2005.